Nadara Yaw Misalignment Challenge

We are pleased to announce the launch of a new WeDoWind challenge, the Nadara Yaw Misalignment Challenge!

Sign up for the launch webinar on 13.04.2026 here:

Find out more and access the WeDoWind platform here:

Yaw misalignment occurs when a wind turbine rotor is not correctly aligned with the wind direction. Even small misalignment angles can lead to significant power losses and increased mechanical loads, making yaw misalignment one of the most impactful sources of underperformance in wind farms. Traditionally, wind turbine performance monitoring relies on standard SCADA data aggregated over 10-minute intervals. While suitable for high-level performance tracking, 10-minute SCADA often lacks the temporal resolution needed to reliably identify yaw misalignment, as control actions, wind direction variability, and transient effects are averaged out.

In contrast, high-frequency SCADA data sampled at 15-second intervals preserves dynamic turbine behaviour, yaw controller response, and short-term power fluctuations. This higher temporal resolution enables more accurate identification of yaw-related underperformance patterns and allows for direct estimation of yaw misalignment angles. Nadara aims to leverage 15-second high-frequency SCADA data to develop robust, data-driven methods for detecting yaw misalignment that go beyond the limitations of traditional 10-minute analysis.

The goal of this challenge is to develop and compare methods for identifying yaw misalignment–driven underperformance using high-frequency SCADA data sampled at 15-second resolution from operating wind turbines.

Nadara has released a brand new public data set in order to carry out this challenge! The dataset is provided in the form of 15-second measurement intervals, and will be made available at the challenge launch meeting.

Participants are expected to develop algorithms capable of reliably detecting yaw misalignment–related underperformance using 15-second high-frequency SCADA data. The submitted approaches should demonstrate the ability to distinguish yaw misalignment effects from normal operational variability and other non-yaw-related performance losses.

In addition, participants should provide consistent and physically meaningful estimates of yaw misalignment angles. The proposed methods are expected to be robust across different turbines, operating conditions, and wind regimes, and to generalize beyond turbine-specific tuning.

The results of the challenge should illustrate the added value of high-frequency SCADA data compared to traditional 10-minute SCADA analysis, highlighting improvements in detection sensitivity and angle estimation. Alongside quantitative performance, clarity of methodology, interpretability, and reproducibility are considered important components of the expected contributions.

We will use the data science platform Renku in order to be able to code together, share code, and easily use the results again in the future.

The rankings will be published in a leaderboard. Winning approaches will have the opportunity to collaborate with Nadara to implement their results as a paid contractor.

Working with nature, backed by shareholders, and with the support of local communities, Nadara is a NextGen Independent Power Producer (IPP+) that develops, owns and operates renewable energy sites across Europe and the US. Our technologies include over 4GW of installed onshore wind, solar photovoltaic, biomass and energy storage, and our IPP+ services encompass energy optimisation, trading, and flexibility solutions that maximise value across the energy chain, supporting energy security and creating long-term value that powers homes, businesses, and change.

In WeDoWind's collaborative problem-solving community, you can access our previous challenges, including:

You can access a summary of the results and publications here: